Is AI ethics a new field?

Its concerns build on older traditions in computer ethics and the philosophy of technology, but the term and much of the contemporary literature gained prominence in the 2010s alongside advances in machine learning.

Does technology ethics assume technology is bad?

No. It studies both the benefits and risks of technologies and asks how they should be designed and governed; many positions emphasize that the same technology can have very different moral effects depending on use and context.

Ethics of Technology and AI

The ethics of technology and AI studies the moral questions raised by technological artifacts and systems, with particular attention to artificial intelligence, automation, and data-driven decision-making.

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Definition

The branch of applied ethics concerned with the moral implications of technology, especially computing, artificial intelligence, and automated systems.

Scope

This area covers the values embedded in technological design, the ethics of artificial intelligence and autonomous systems, algorithmic fairness, privacy and surveillance, accountability for automated decisions, and the broader question of whether technologies are neutral tools or carry political and moral significance. It includes proposed AI-ethics principles and frameworks. As a reference subject it describes these issues and debates rather than offering design or policy prescriptions.

Sub-topics

Core questions

Are technologies morally neutral tools, or do they embody values and politics?
Who is responsible when an automated or AI system causes harm?
How should fairness, transparency, and accountability apply to algorithmic decisions?
What principles, if any, should govern the development and deployment of AI?

Key theories

Artifacts have politics: Langdon Winner's thesis that technological artifacts can embody specific forms of power and authority, so technologies are not value-neutral but can settle social and political arrangements.
Principle-based AI ethics frameworks: Floridi and Cowls synthesize widely proposed AI principles into beneficence, non-maleficence, autonomy, justice, and explicability, drawing on and extending the bioethics tradition.

History

Computer ethics developed from the 1980s, and broader philosophy of technology from work by figures such as Winner. The rapid deployment of machine learning in the 2010s prompted an explosion of AI-ethics scholarship and the proliferation of principle-based guidelines surveyed by Jobin and colleagues.

Debates

Whether high-level principles are sufficient: Convergence on broad AI principles is widespread, but scholars debate whether such principles can be operationalized or whether they risk becoming 'ethics washing' without enforcement and concrete practice.

Key figures

Langdon Winner
Luciano Floridi
Helen Nissenbaum
Shannon Vallor

Seminal works

winner1980
floridi2019
jobin2019

Frequently asked questions

Is AI ethics a new field?: Its concerns build on older traditions in computer ethics and the philosophy of technology, but the term and much of the contemporary literature gained prominence in the 2010s alongside advances in machine learning.
Does technology ethics assume technology is bad?: No. It studies both the benefits and risks of technologies and asks how they should be designed and governed; many positions emphasize that the same technology can have very different moral effects depending on use and context.